def sample2():
"""
Here's the transmitted intensity versus wavelength through a single-layer
film which has some complicated wavelength-dependent index of refraction.
(I made these numbers up, but in real life they could be read out of a
graph / table published in the literature.) Air is on both sides of the
film, and the light is normally incident.
"""
#index of refraction of my material: wavelength in nm versus index.
material_nk_data = array([[200, 2.1+0.1j],
[300, 2.4+0.3j],
[400, 2.3+0.4j],
[500, 2.2+0.4j],
[750, 2.2+0.5j]])
material_nk_fn = interp1d(material_nk_data[:,0].real,
material_nk_data[:,1], kind='quadratic')
d_list = [inf, 300, inf] #in nm
lambda_list = linspace(200, 750, 400) #in nm
T_list = []
for lambda_vac in lambda_list:
n_list = [1, material_nk_fn(lambda_vac), 1]
T_list.append(coh_tmm('s', n_list, d_list, 0, lambda_vac)['T'])
plt.figure()
plt.plot(lambda_list, T_list)
plt.xlabel('Wavelength (nm)')
plt.ylabel('Fraction of power transmitted')
plt.title('Transmission at normal incidence')
def sample1():
"""
Here's a thin non-absorbing layer, on top of a thick absorbing layer, with
air on both sides. Plotting reflected intensity versus wavenumber, at two
different incident angles.
"""
# list of layer thicknesses in nm
d_list = [inf, 100, 300, inf]
# list of refractive indices
n_list = [1, 2.2, 3.3+0.3j, 1]
# list of wavenumbers to plot in nm^-1
ks = linspace(0.0001, .01, num=400)
# initialize lists of y-values to plot
Rnorm = []
R45 = []
for k in ks:
# For normal incidence, s and p polarizations are identical.
# I arbitrarily decided to use 's'.
Rnorm.append(coh_tmm('s', n_list, d_list, 0, 1/k)['R'])
R45.append(unpolarized_RT(n_list, d_list, 45*degree, 1/k)['R'])
kcm = ks * 1e7 #ks in cm^-1 rather than nm^-1
plt.figure()
plt.plot(kcm, Rnorm, 'blue', kcm, R45, 'purple')
plt.xlabel('k (cm$^{-1}$)')
plt.ylabel('Fraction reflected')
plt.title('Reflection of unpolarized light at 0$^\circ$ incidence (blue), '
'45$^\circ$ (purple)')
def sample6():
"""
An example reflection plot with a surface plasmon resonance (SPR) dip.
Compare with http://doi.org/10.2320/matertrans.M2010003 ("Spectral and
Angular Responses of Surface Plasmon Resonance Based on the Kretschmann
Prism Configuration") Fig 6a
"""
# list of layer thicknesses in nm
d_list = [inf, 5, 30, inf]
# list of refractive indices
n_list = [1.517, 3.719+4.362j, 0.130+3.162j, 1]
# wavelength in nm
lam_vac = 633
# list of angles to plot
theta_list = linspace(30*degree, 60*degree, num=300)
# initialize lists of y-values to plot
Rp = []
for theta in theta_list:
Rp.append(coh_tmm('p', n_list, d_list, theta, lam_vac)['R'])
plt.figure()
plt.plot(theta_list/degree, Rp, 'blue')
plt.xlabel('theta (degree)')
plt.ylabel('Fraction reflected')
plt.xlim(30, 60)
plt.ylim(0, 1)
plt.title('Reflection of p-polarized light with Surface Plasmon Resonance\n'
'Compare with http://doi.org/10.2320/matertrans.M2010003 Fig 6a')
def sample4():
"""
Here is an example where we plot absorption and Poynting vector
as a function of depth.
"""
d_list = [inf, 100, 300, inf] #in nm
n_list = [1, 2.2+0.2j, 3.3+0.3j, 1]
th_0 = pi/4
lam_vac = 400
pol = 'p'
coh_tmm_data = coh_tmm(pol, n_list, d_list, th_0, lam_vac)
ds = linspace(-50, 400, num=1000) #position in structure
poyn = []
absor = []
for d in ds:
layer, d_in_layer = find_in_structure_with_inf(d_list, d)
data = position_resolved(layer, d_in_layer, coh_tmm_data)
poyn.append(data['poyn'])
absor.append(data['absor'])
# convert data to numpy arrays for easy scaling in the plot
poyn = array(poyn)
absor = array(absor)
plt.figure()
plt.plot(ds, poyn, 'blue', ds, 200*absor, 'purple')
plt.xlabel('depth (nm)')
plt.ylabel('AU')
plt.title('Local absorption (purple), Poynting vector (blue)')
def compute_electric_field_p_pol(device,
grid_resolution_um,
device_depth_um,
device_depth_voxels,
angle_radians,
lambda_vac_um,
reverse=False):
d_list = [
np.inf, 1, *(grid_resolution_um * np.ones(device_depth_voxels)), 1,
np.inf
]
n_list = [1, 1, *device, 1, 1]
if reverse:
coh_tmm_data = coh_tmm_reverse('p', n_list, d_list, angle_radians,
lambda_vac_um)
else:
coh_tmm_data = coh_tmm('p', n_list, d_list, angle_radians,
lambda_vac_um)
get_E_pts = np.linspace(1, 1 + device_depth_um, device_depth_voxels)
Ex_data = np.zeros(device_depth_voxels, dtype=np.complex)
Ez_data = np.zeros(device_depth_voxels, dtype=np.complex)
for d_idx in range(0, device_depth_voxels):
d = get_E_pts[d_idx]
layer = 2 + d_idx
d_in_layer = 0.5 * grid_resolution_um
data = position_resolved(layer, d_in_layer, coh_tmm_data)
Ex_data[d_idx] = data['Ex']
Ez_data[d_idx] = data['Ez']
adjoint_meausre_point_um = 1 + device_depth_um + 1
layer, d_in_layer = find_in_structure_with_inf(d_list,
adjoint_meausre_point_um)
data_adjoint_measure = position_resolved(layer, d_in_layer, coh_tmm_data)
Ex_adjoint_measure = data_adjoint_measure['Ex']
Ez_adjoint_measure = data_adjoint_measure['Ez']
E_adjoint_measure = Ex_adjoint_measure
if reverse:
Ex_data = np.flip(Ex_data)
Ez_data = np.flip(Ez_data)
return Ex_data, Ez_data, coh_tmm_data['T'], E_adjoint_measure
"""
degree = pi/180
# list of layer thicknesses in nm
d_list = [inf, 100, 300, inf]
# list of refractive indices
n_list = [1, 2.2, 3.3+0.3j, 1]
# list of wavenumbers to plot in nm^-1
ks = linspace(0.0001, .01, num=400)
# initialize lists of y-values to plot
rnorm = []
r45 = []
for k in ks:
# For normal incidence, s and p polarizations are identical.
# I arbitrarily decided to use 's'.
rnorm.append(tmm.coh_tmm('s', n_list, d_list, 0, 1/k)['R'])
r45.append(tmm.unpolarized_RT(n_list, d_list, 45*degree, 1/k)['R'])
kcm = ks * 1e7 #ks in cm^-1 rather than nm^-1
plt.figure()
plt.plot(kcm, rnorm, 'blue', kcm, r45, 'purple')
plt.xlabel('k (cm$^{-1}$)')
plt.ylabel('Fraction reflected')
plt.title('Reflection of unpolarized light at 0$^\circ$ incidence (blue), '
'45$^\circ$ (purple)')
plt.show()
#if __name__ == '__main__':
# main()